A new framework for sign language alphabet hand posture recognition using geometrical features through artificial neural network (part 1)

Neural Computing and Applications - Hand pose tracking is essential in sign languages. An automatic recognition of performed hand signs facilitates a number of applications, especially for people...     

A New Traffic Sign Recognition Technique Taking Shuffled Frog-Leaping Algorithm into Account

Everyday humans use cars to move faster, and the world is a chaotic place, and a little distraction or a mistake could be the reason for an accident and bring people great pain. An assistance system that can distinguish and detect signs on the roads and brings the driver's attention to road signs and make them aware of their meaning could be beneficial. The most important part of the Traffic Sign Recognition System is the algorithm. In this paper, a new way toward Traffic Sign Recognition algorithm taking the advantages of Color Segmentation, support vector machines, and histograms of oriented gradients on the GTSRB dataset is proposed. The unsupervised shuffled frog-leaping algorithm is employed for segmenting the images. The results show remarkable improvements by using meta-heuristic algorithms.

     

Investigation of mechanical properties and fatigue life of ECARed AA5083 aluminium alloy

Equal‐channel angular rolling (ECAR) is a continuous severe plastic deformation process. In this process, severe shear strains apply to the sheet. This strain increases the yield or ultimate strength of sheet without significant change in sheet dimension. In this paper, the effect of ECAR process on mechanical properties and fatigue life of manufactured sheets will be studied. Four AA5083 samples have been prepared and annealed for obtaining stress‐free samples. Three samples have been rolled by the ECAR process with one, two and three passes of rolling, respectively. Mechanical tests including tensile test, hardness and axial fatigue tests have been carried out on prepared samples. Fatigue tests have been implemented according to a strain‐based approach with a constant strain ratio equal to 0.75 and 0.5 Hz frequency of loading. All of the tests have been carried out in controlled laboratory conditions. Results show that the ultimate tensile strength of samples increases with increasing the pass of rolling. Also, the maximum elongation of samples decreases. Maximum elongation was 17% in annealed samples, while it decreases to 10% in samples with three passes of rolling. The hardness of samples has been measured, and the results show an increase in hardness for a higher pass of the ECAR process. Fatigue test results show that fatigue life of AA5083 samples decreases in manufactured sheets of the ECAR process. Also, cyclic softening has been observed in the ECARed sample. The fracture surfaces of samples after fatigue test have been observed with a scanning electron microscope. A comparison of fracture surfaces confirms that the crack growth was intergranular in annealed samples while it changes in ECARed samples to transgranular.     

An Optimization Model for the Increment in the Yield of Distillation Columns Based on Reverse Engineering in the Petroleum Industry

Abstract

Optimization in the chemical and petroleum industry is gaining increased interest because of its importance in maintaining product quality and enhancing production levels while improving profit margins. In this article, simulation of the atmospheric distillation unit of an existing petroleum refinery is carried out. Optimization was performed on the prepared simulation through the use of a sequential quadratic programming approach (SQP). The objective function consisted of energy minimization and production level maximization. The results obtained from optimization were implemented on the real process and it was demonstrated that the suggested changes increased overhead production levels and maintained product quality. Furthermore, a net economical balance between the increment of overhead products and the energy consumption showed an energy savings in the refinery.     

Enhanced Tacit Secrets: System-assigned passwords you can’t write down,but don’t need to

International Journal of Information Security - We explore the feasibility of Tacit Secrets: system-assigned passwords that you can remember, but cannot write down or otherwise communicate. We...     

Hollow Twist Extrusion: Introduction,Strain Distribution,and Process Parameters Investigation

Metals and Materials International - Twist Extrusion is kind of severe plastic deformation process which enhances the strength of materials by applying a shear plastic strain and consequently grain...     

Oxygen reduction electrode in advanced chlor‐alkali with ruthenium as electro‐catalyst

The platinum (Pt) diffusion gas electrodes are frequently used in chlor‐alkali process industry. The platinum (Pt) diffusion gas electrodes used in advanced chlor‐alkali process has encountered many disadvantages such as flooding, which is the result of peroxide production phenomenon. The flooding reduces the process efficiency. In this article new electrodes are used to overcome some of the above‐mentioned disadvantages to increase efficiency. The effects of seven process parameters are also individually studied. The results show the brine concentration increase CCE by increasing, anolyte, oxygen temperatures, and flow rates. The brine concentration decreases as the current density increases. The Ru/C catalyst performance is higher than Pt/C catalyst. Besides, Ru effectively prevents the aggregation and growth of platinum nano‐particles in the thermal heating process. The higher activity, good stability, and the better caustic current efficiency of the Ru/C catalyst make it more suitable cathode in advanced chlor‐alkali process.     

Optimization of caustic current efficiency in a zero-gap advanced chlor-alkali cell with application of genetic algorithm assisted by artificial neural networks

The effects of various process parameters on caustic current efficiency (CCE) in a zero-gap oxygen-depolarized chlor-alkali cell employing a state-of-the-art silver plated nickel screen electrode (ESNS^®) were studied. For doing a thorough research, we selected the process parameters from both cathodic and anodic compartments. Seven process parameters were studied including anolyte pH, temperature, flow rate and brine concentration from the anode side, oxygen temperature and flow rate from the cathode side and the applied current density. The effect of these parameters on CCE was determined quantitatively. A feed forward neural network model with the Levenberg–Marquardt (LM) back propagation training method was developed to predict CCE. Then genetic algorithm (GA) was implemented to neural network model. The highest CCE (98.53%) was found after 20 times running GA at the following conditions: brine concentration (287 g/L), anolyte temperature (80 °C), anolyte pH (2.7), anolyte flow rate (408 cm³/min), oxygen flow rate (841 cm³/min), oxygen temperature (79 °C), and current density (0.33 A/cm²).